The applicant's long-term goal is to understand the neurocardiac mechanism underlying sudden cardiac death. The applicant states that neurocardiological approaches over the past two decades, in both animal and human studies, have clearly shown that psychosocial stressors, higher cerebral integrative-centers, and the autonomic nerves have important regulatory roles, perhaps even causal ones, in the process of lethal ventricular fibrillation (VF). The heart rate variability (HRV) is primarily regulated by the nervous system. An altered range, synchrony or pattern of HRV is predictive of risk in prospective clinical studies. Of these, the applicant believes the altered pattern of variability, represented by a reduction in the chaotic dimension of the heartbeats, seems to best predict VF, but this measure has only been studied in high-risk patient groups. The applicant now wishes to study this HRV measure, along with other promising stochastic and deterministic candidate-measures, in data collected during experimental ischemia in the conscious pig, a preparation in which the neurocardiac variables regulating vulnerability to VF can be systematically controlled. The applicant also wishes to integrate his studies of HRV with a mathematical theory of heartbeat generation and arrhythmogenesis. The applicant developed a strategy in which he can remap the variables of the theoretical model into the QT and RR-QT subintervals of each heartbeat. In support of this strategy the applicant has found 1) a predicted exclusion area of the QT vs RR-QT dynamics; 2) a breakdown of this exclusion area by neurocardiac variables known to increase risk of VF, and 3) evoked arrhythmias when the QT vs RR-QT dynamics enter the exclusion area. The applicant's final aim is to model these phenomena, using a mathematical simulation of an excitable medium that has T-waves.